In [4]:
%matplotlib inline
In [2]:
import os
import numpy as np
import pandas as pd
import nibabel as nib
import matplotlib.pyplot as plt
import nipype.interfaces.fsl as fsl  # fsl
from nipype import Node, Workflow  # components to construct workflow
from nipype.interfaces.io import DataSink  # datasink
from nilearn.plotting import plot_stat_map, view_img
from nilearn.image import math_img, coord_transform


# PARAMETERS
zThresh = 2.3  # a.k.a., p=0.01 uncorrected threshold
contInd = '1'  # contrast of interest

# FILE AND DIRECTORY BUSINESS
# original data directory
dataDir = '/tmp/Data/ds114'
# Output directory
outDir = os.path.join(dataDir,'WorkflowOutput')
# Datasink directory
datasinkDir = os.path.join(outDir,'OVGvsOWR_Test')
# stats_dir directory
statsDir = os.path.join(datasinkDir,'stats_dir/stats')
# Z-stat image
imgZStat = os.path.join(statsDir, 'zstat' + contInd + '.nii.gz')


# FINDING CLUSTERS IN THE ANALYSIS RESULTS
# cluster node
cluster = Node(fsl.Cluster(in_file=imgZStat,
                           threshold=zThresh,
                           out_index_file=True,
                           out_threshold_file=True,
                           out_localmax_txt_file=True),
               name='cluster')

# data sink node
datasink = Node(DataSink(base_directory=statsDir),
                name='datasink')

# workflow connecting clustering to the datasink
clusterWF = Workflow(name="clusterWF", base_dir=outDir)
clusterWF.connect(cluster, 'index_file', datasink, 'index_file')
clusterWF.connect(cluster, 'threshold_file', datasink, 'threshold_file')
clusterWF.connect(cluster, 'localmax_txt_file', datasink, 'localmax_txt_file')
clusterWF.run()

/usr/local/lib/python3.5/dist-packages/sklearn/externals/joblib/__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.
  warnings.warn(msg, category=DeprecationWarning)

191114-19:24:38,138 nipype.workflow INFO:
	 Workflow clusterWF settings: ['check', 'execution', 'logging', 'monitoring']
191114-19:24:38,144 nipype.workflow INFO:
	 Running serially.
191114-19:24:38,145 nipype.workflow INFO:
	 [Node] Setting-up "clusterWF.cluster" in "/tmp/Data/ds114/WorkflowOutput/clusterWF/cluster".
191114-19:24:38,147 nipype.workflow INFO:
	 [Node] Outdated cache found for "clusterWF.cluster".
191114-19:24:38,158 nipype.workflow INFO:
	 [Node] Running "cluster" ("nipype.interfaces.fsl.model.Cluster"), a CommandLine Interface with command:
cluster --in=/tmp/Data/ds114/WorkflowOutput/OVGvsOWR_Test/stats_dir/stats/zstat1.nii.gz --oindex=/tmp/Data/ds114/WorkflowOutput/clusterWF/cluster/zstat1_index.nii.gz --olmax=/tmp/Data/ds114/WorkflowOutput/clusterWF/cluster/zstat1_localmax.txt --othresh=/tmp/Data/ds114/WorkflowOutput/clusterWF/cluster/zstat1_threshold.nii.gz --thresh=2.3000000000
191114-19:24:38,232 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.232083:Cluster Index	Voxels	MAX	MAX X (vox)	MAX Y (vox)	MAX Z (vox)	COG X (vox)	COG Y (vox)	COG Z (vox)
191114-19:24:38,234 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:120	523	6.31	12	35	28	15	37.8	29.1
191114-19:24:38,235 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:119	254	7.44	16	14	31	15	16.6	30.6
191114-19:24:38,236 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:118	198	4.9	18	18	14	26.5	22.5	13.9
191114-19:24:38,237 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:117	158	5.09	10	17	15	12.3	18.3	18.7
191114-19:24:38,238 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:116	136	4.51	26	33	20	25.7	37.8	19.8
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	 stdout 2019-11-14T19:24:38.234449:114	40	3.84	31	37	30	29.8	38.3	27.7
191114-19:24:38,242 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:113	31	4.04	16	47	27	16.1	46.5	24.4
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	 stdout 2019-11-14T19:24:38.234449:7	1	3.78	20	36	16	20	36	16
191114-19:24:38,342 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:6	1	2.41	8	29	16	8	29	16
191114-19:24:38,343 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:5	1	2.51	30	23	16	30	23	16
191114-19:24:38,343 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:4	1	2.37	24	32	27	24	32	27
191114-19:24:38,344 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:3	1	2.45	19	34	27	19	34	27
191114-19:24:38,345 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:2	1	2.56	10	15	28	10	15	28
191114-19:24:38,346 nipype.interface INFO:
	 stdout 2019-11-14T19:24:38.234449:1	1	2.34	12	15	19	12	15	19
191114-19:24:38,487 nipype.workflow INFO:
	 [Node] Finished "clusterWF.cluster".
191114-19:24:38,488 nipype.workflow INFO:
	 [Node] Setting-up "clusterWF.datasink" in "/tmp/Data/ds114/WorkflowOutput/clusterWF/datasink".
191114-19:24:38,491 nipype.workflow INFO:
	 [Node] Outdated cache found for "clusterWF.datasink".
191114-19:24:38,495 nipype.workflow INFO:
	 [Node] Running "datasink" ("nipype.interfaces.io.DataSink")
191114-19:24:38,500 nipype.workflow INFO:
	 [Node] Finished "clusterWF.datasink".
Out[2]:
<networkx.classes.digraph.DiGraph at 0x7f7a55bb7f98>
In [5]:
# VISUALIZATION
# T1 weighted image for background
anatDir = os.path.join(dataDir,'derivatives_selected/fmriprep/sub-09/anat/')
imageT1 = os.path.join(anatDir,
                       'sub-09_space-MNI152NLin2009cAsym_desc-preproc_T1w.nii.gz')

# Thresholded zstat image
fThZStat=os.path.join(statsDir,'threshold_file/zstat' + contInd + '_threshold.nii.gz')
thImageStat=nib.load(fThZStat)

# global maximum cooridnates
X_zstat = nib.load(imgZStat).get_data()  # loading the zstat image
globalMax = np.unravel_index(np.argmax(X_zstat), X_zstat.shape) # voxel space
globalMaxMNI = coord_transform(globalMax[0],
                               globalMax[1],
                               globalMax[2],
                               thImageStat.affine)  # MNI space

# blob overlay at global max
plot_stat_map(thImageStat, bg_img=imageT1,
              colorbar=True, threshold=2.3, black_bg=True,
              draw_cross=True,
              cut_coords=globalMaxMNI)
Out[5]:
<nilearn.plotting.displays.OrthoSlicer at 0x7f7a546ee518>
In [6]:
# interactive visualization
view_img(thImageStat, bg_img=imageT1, cmap='black_red',
         symmetric_cmap=False, annotate=True,
         colorbar=True, threshold=2.3, black_bg=True,
         cut_coords=globalMaxMNI)
Out[6]:
In [ ]: